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PacktPublishing / Deep-Reinforcement-Learning-Hands-On

Hands-on Deep Reinforcement Learning, published by Packt
MIT License
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Chapter08 - run_model.py return size mismatch #46

Closed lamhk closed 5 years ago

lamhk commented 5 years ago

Hi after running the "train_model_conv.py", I tried to test the saved models using "run_model.py" using the below command but got size mismatch error as stated below. Any idea how I could fix it? Many thanks in advance.

Chapter08$ python3 run_model.py -d data/YNDX_160101_161231.csv -m saves/runs/mean_val-0.824.data -b 10 -n test --conv

Reading data/YNDX_160101_161231.csv Read done, got 131542 rows, 99752 filtered, 0 open prices adjusted Traceback (most recent call last): File "run_model.py", line 35, in net.load_state_dict(torch.load(args.model, map_location=lambda storage, loc: storage)) File "/home/lamhk/Deep-RL-Hands-On/venv/Deep-RL/lib/python3.5/site-packages/torch/nn/modules/module.py", line 719, in load_state_dict self.class.name, "\n\t".join(error_msgs))) RuntimeError: Error(s) in loading state_dict for DQNConv1D: size mismatch for fc_val.0.weight: copying a param of torch.Size([512, 256]) from checkpoint, where the shape is torch.Size([512, 5376]) in current model. size mismatch for fc_adv.0.weight: copying a param of torch.Size([512, 256]) from checkpoint, where the shape is torch.Size([512, 5376]) in current model.

Shmuma commented 5 years ago

Hi!

Amount of bars passed to the model (-b option) have to match amount used during the trainig. This value is set here: https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On/blob/master/Chapter08/train_model_conv.py#L16, and equal to 50 by default. So, you should pass -b 50 in command line to match.

Alternative would be to change the constant in train_model_conv.py.

lamhk commented 5 years ago

Hi Shumuma, it works as explained about. Many thanks.